Modelling Stock Indexes Volatility of Emerging Markets

Abstract

This study aims to investigate the use of ARCH (autoregressive conditional heteroscedasticity) family models for forecasting volatility of four regional emerging stock markets i.e. KSE 100, BSE-SENSEX, DSE 20 and SSE Composite index. The ARCH, GARCH, EGARCH, TGARCH and PARCH models are used and the best model is selected on the basis of the Akaike information criterion (AIC) and Schwartz information criterion (SIC) over the sample period covering from January 1996 to December 2015. Empirical evidence suggested on the basis of AIC, TGARCH outperformed other models in case of BSE SENSEX, DSE 20 and SSE COMPOSITE index. TGARCH model is considered as the best closely followed by PARCH model, whereas PARCH is also considered as the best performing model for BSE SENSEX, KSE 100 and SSE COMPOSITE index. Meanwhile, on the basis of SIC, GARCH is the best performing model for BSE SENSEX and SSE COMPOSITE, whereas PARCH and EGARCH for KSE 100 and DSE 20 respectively. This study will help portfolio managers, investors and policy makers to make their investment strategies in these emerging markets accordingly.